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3D geometric morphometrics in veterinary science: applications, standardization, and future directions

dc.contributor.authorSzara, T.
dc.contributor.authorHadziomerovic, N.
dc.contributor.authorBakici, C.
dc.contributor.authorGuzel, B. Can
dc.contributor.authorGundemir, O.
dc.date.accessioned2026-10-23T18:13:36Z
dc.date.available2026-10-23T18:13:36Z
dc.date.issued2026
dc.departmentSiirt Üniversitesi
dc.description.abstractThree-dimensional geometric morphometric methods have emerged as a pivotal tool in veterinary anatomy, taxonomy, clinical research, and studies of morphological diversity. This article summarizes the key stages, applications, clinical potential, and recommendations for data standardization in 3D morphometrics. Datasets are typically acquired using radiological modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and 3D surface scanning, each offering specific advantages and constraints contingent on the research context. Standardized landmark sets are essential in 3D morphometric studies to ensure reproducibility and comparability of results across independent investigations. Consistent use of reference landmarks enables repeatable analyses, but the number of landmarks directly influences the required sample size and statistical power. Consequently, a minimal yet balanced landmark configuration is critical. This article proposes a standardized, minimal landmark set for the skulls of horses, cattle, and sheep to enhance inter-study reproducibility and comparability. Landmark selection prioritizes anatomically distinct points to avoid excessive landmarking, which may complicate analyses or compromise interpretability. Applications of 3D morphometric methods include orthopedic surgical planning, biomechanical modeling, and assessment of congenital anomalies, providing enhanced precision in diagnostics and research. In conclusion, 3D geometric morphometric methods represent a robust analytical framework in veterinary anatomy, morphology, and clinical research. Their significance is poised to grow through integration with automated landmarking, artificial intelligence-driven analyses, and international data-sharing networks, thereby advancing scientific inquiry in novel dimensions.
dc.identifier.doi10.24425/pjvs.2026.158509
dc.identifier.endpage156
dc.identifier.issn1505-1773
dc.identifier.issn2300-2557
dc.identifier.issue1
dc.identifier.orcid0000-0002-2504-120X
dc.identifier.pmid41860003
dc.identifier.scopus2-s2.0-105033861766
dc.identifier.scopusqualityQ3
dc.identifier.startpage147
dc.identifier.urihttps://doi.org/10.24425/pjvs.2026.158509
dc.identifier.urihttps://hdl.handle.net/20.500.12604/12077
dc.identifier.volume29
dc.identifier.wosWOS:001743725700016
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherPolska Akad Nauk, Polish Acad Sciences, Univ Warmia & Mazury Olsztyn
dc.relation.ispartofPolish Journal of Veterinary Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20261017
dc.subjectBiomechanical Modeling
dc.subjectCranial Landmarks
dc.subject3D Geometric Morphometrics
dc.subjectOrtho-Pedic Surgical Planning
dc.subjectVeterinary Anatomy
dc.title3D geometric morphometrics in veterinary science: applications, standardization, and future directions
dc.typeReview Article

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